Bigdata & Hadoop Training

The Big Data training and the Hadoop training courses offered at Victorrious Digiital have a huge demand in the job market today. Being one of the best Big Data Hadoop training institutes, Victorrious Digiital enables you to explore a unique way of learning new skills with the professional training approach. Going through the well designed, industry aligned Big Data courses certainly trains students thoroughly for the highly competitive industry. A training in Big Data and Analytics can lead to better job opportunities. To learn the latest in this technology, join Victorrious Digiital today.

Hadoop is open source (Cost saving / Cheaper)

Hadoop solves Big Data problem which is very difficult or impossible to solve using highly paid tools in market

It can process Distributed data and no need to store entire data in centralized storage as it is there with other tools.

Now a days there is job cut in market in so many existing tools and technologies because clients are moving towards a cheaper and efficient solution in market named HADOOP

Why Hadoop?

Solution for BigData Problem

Open Source Technology

Based on open source platforms

Contains several tool for entire ETL data processing Framework

It can process Distributed data and no need to store entire data in centralized storage as it is required for SQL based tools.

Big Data

Distributed computing

Data management – Industry Challenges

Overview of Big Data

Characteristics of Big Data

Types of data

Sources of Big Data

Big Data examples

What is streaming data?

Batch vs Streaming data processing

Overview of Analytics

Big data Hadoop opportunities

Hadoop

Why we need Hadoop

Data centres and Hadoop Cluster overview

Overview of Hadoop Daemons

Hadoop Cluster and Racks

Learning Linux required for Hadoop

Hadoop ecosystem tools overview

Understanding the Hadoop configurations and Installation.

HDFS (Storage)

HDFS

HDFS Daemons – Namenode, Datanode, Secondary Namenode

Hadoop FS and Processing Environment’s UIs

Fault Tolerant

High Availability

Block Replication

How to read and write files

Hadoop FS shell commands

YARN (Hadoop Processing Framework)

YARN

YARN Daemons – Resource Manager, NodeManager etc.

Job assignment & Execution flow

Apache Hive

Data warehouse basics

OLTP vs OLAP Concepts

Hive

Hive Architecture

Metastore DB and Metastore Service

Hive Query Language (HQL)

Managed and External Tables

Partitioning & Bucketing

Query Optimization

Hiveserver2 (Thrift server)

JDBC , ODBC connection to Hive

Hive Transactions

Hive UDFs

Working with Avro Schema and AVRO file format

Apache Pig

Apache Pig

Advantage of Pig over MapReduce

Pig Latin (Scripting language for Pig)

Schema and Schema-less data in Pig

Structured , Semi-Structure data processing in Pig

Pig UDFs

HCatalog

Pig vs Hive Use case

Sqoop

Sqoop commands

Sqoop practical implementation

Importing data to HDFS

Importing data to Hive

Exporting data to RDBMS

Sqoop connectors

Flume

Flume commands

Configuration of Source, Channel and Sink

Fan-out flume agents

How to load data in Hadoop that is coming from web server or other storage

How to load streaming data from Twitter data in HDFS using Hadoop

Oozie

Oozie

Action Node and Control Flow node

Designing workflow jobs

How to schedule jobs using Oozie

How to schedule jobs which are time based

Oozie Conf file

Scala

Scala

Syntax formation, Datatypes , Variables

Classes and Objects

Basic Types and Operations

Functional Objects

Built-in Control Structures

Functions and Closures

Composition and Inheritance

Scala’s Hierarchy

Traits

Packages and Imports

Working with Lists, Collections

Abstract Members

Implicit Conversions and Parameters

For Expressions Revisited

The Scala Collections API

Extractors

Modular Programming Using Objects

Spark

Spark

Architecture and Spark APIs

Spark components

Spark master

Driver

Executor

Worker

Significance of Spark context

Concept of Resilient distributed datasets (RDDs)

Properties of RDD

Creating RDDs

Transformations in RDD

Actions in RDD

Saving data through RDD

Key-value pair RDD

Invoking Spark shell

Loading a file in shell

Performing some basic operations on files in Spark shell

Spark application overview

Job scheduling process

DAG scheduler

RDD graph and lineage

Life cycle of spark application

How to choose between the different persistence levels for caching RDDs

Our Courses List

Know Us

We have successfully trained over 2500 students and have completed around 300 batches. We make sure that our batch timings are flexible and suitable for all types of individuals be it students or working men/women. We assure 100% job assistance to all those who are part of Victorrious Digiital. We offer best companies for placements. Not only that we even provide certification for the course….Click Here